The Virtue of Complexity in Return Prediction
This article explores how researchers forecast market returns by aggregating expected returns from individual stocks.
This article explores how researchers forecast market returns by aggregating expected returns from individual stocks.
Let’s break down how to build a robust factor portfolio—without getting lost in the weeds. We investigate which equity factors have the strongest historical returns and diversification benefits from a long-only perspective.
This article explores how researchers forecast market returns by aggregating expected returns from individual stocks.
The financial research literature has found that the performance of assets (and factors) can vary substantially across regimes - factor premiums can be regime dependent. Unfortunately, the real-time identification of the current economic regime is one of the biggest challenges in finance.
This article explores the difference between tradable and on-paper (theoretical) risk factors in investing. Risk factors are strategies that help explain stock market returns, but many work only in theory and not in real life.
The main benefit of constructing industry momentum portfolios based on standard ICS is that it is straightforward and reproducible. However, that benefit may come at the cost of accuracy and oversimplification of complex industry relationships between companies.
Investing isn’t about being mostly right. In fact you can be mostly wrong and beat portfolios that were mostly right! Today, we’ll explore how investors can potentially improve portfolio outcomes by targeting two seemingly contradictory but deeply complementary systems as outlined in the latest Mauboussin-Callahan paper, Probabilities & Payoffs: The Practicality and Psychology of Expected Value. But understanding this counterintuitive reality requires a shift in mindset—one that embraces uncertainty and focuses on the power of diversification.
When information about a company comes out gradually, investors might not react strongly, leading to momentum. Other factors, like how a company's value is perceived, also play a role, but to a lesser extent.
For equity investors there have been two major narratives over the last 17 calendar year period 2008-2024. The first is that US stocks have far outperformed international stocks. The other narrative has been the outperformance of growth stocks relative to value stocks.
The empirical research we have reviewed shows that the (hidden) costs of index construction and rebalancing policies to investors are about 10 times the expense ratios.
Dividends are the comfort food of investing. Who wouldn’t love feeling like they’re getting a seemingly “free” payout just for holding onto a stock? As with all good things, there's a little more—perhaps a whole lot more—to the story. Here’s why: even in a tax-free setting, selling stocks before dividend payouts can lead to abnormal returns.
Trend following, at its core, is a strategy where investors buy an asset when it's going up and sell when it’s going down. But unlike panic-driven investors who sell at the worst possible moment, trend followers adhere to a rules-based approach in an attempt to remove emotion from the equation.
US exceptionalism provided the same explanation for the outperformance of US stocks in the 1990s. However, that regime changed. From 2000-2007, while the S&P 500 Index returned just 1.9% per annum (underperforming riskless one-month Treasury bills by 1.3% per annum), the MSCI EAFE Index returned 5.6% per annum, and the MSCI Emerging Markets Index returned 15.3% per annum.
The listing domicile explained about 50% of the valuation gap. In other words, US-listed stocks are substantially more expensive than internationally listed stocks for no reason other than the place of listing.
What matters is not the expectation of future growth, but the deviation between projected growth and realized growth, which, by definition is a surprise, and, thus, is not forecastable.
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Simple, easy-to-implement, systematic formula-based investing can still generate market outperformance, providing investors with efficient exposure to well-documented factor premiums.
One critical, yet often overlooked, choice is how stocks are weighted in the objective function during training, with equally weighted (EW) approaches being the norm. This paper investigates how such choices impact cross-sectional return predictability and the performance of trading strategies derived from these predictions, focusing on the interplay between objective function design and model outcomes.
Managers are more likely to vote for analysts who exhibit greater “say-buy/whisper-sell” behavior toward these man agers. This suggests that analysts reduce the accuracy of their public recommendations, thereby maintaining the value of their private advice to funds.
Systematic factor-driven value strategies have underperformed broad market indices (such as the S&P 500) over the past 15+ years. That has led many to question [...]
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